Package: lite 1.1.1
lite: Likelihood-Based Inference for Time Series Extremes
Performs likelihood-based inference for stationary time series extremes. The general approach follows Fawcett and Walshaw (2012) <doi:10.1002/env.2133>. Marginal extreme value inferences are adjusted for cluster dependence in the data using the methodology in Chandler and Bate (2007) <doi:10.1093/biomet/asm015>, producing an adjusted log-likelihood for the model parameters. A log-likelihood for the extremal index is produced using the K-gaps model of Suveges and Davison (2010) <doi:10.1214/09-AOAS292>. These log-likelihoods are combined to make inferences about extreme values. Both maximum likelihood and Bayesian approaches are available.
Authors:
lite_1.1.1.tar.gz
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lite.pdf |lite.html✨
lite/json (API)
NEWS
| # Install 'lite' in R: |
| install.packages('lite', repos = c('https://paulnorthrop.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/paulnorthrop/lite/issues
clusteredextremal-indexextreme-value-statisticsextremesfrequentistgeneralised-paretoinferencelikelihoodlog-likelihoodthresholdtime-series
Last updated 4 months agofrom:1efc46871f. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 14 2024 |
| R-4.5-win | OK | Nov 14 2024 |
| R-4.5-linux | OK | Nov 14 2024 |
| R-4.4-win | OK | Nov 14 2024 |
| R-4.4-mac | OK | Nov 14 2024 |
| R-4.3-win | OK | Nov 14 2024 |
| R-4.3-mac | OK | Nov 14 2024 |
Exports:blitefitBernoullifitGPflitegpObsInfologLikVectorreturnLevel
Dependencies:abindbackportsbayesplotchandwichcheckmateclicolorspacedistributionaldplyrexdexfansifarvergenericsggplot2ggridgesgluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivpillarpkgconfigplyrposteriorR6RColorBrewerRcppRcppArmadilloRcppRollreshape2revdbayesrlangrustsandwichscalesstringistringrtensorAtibbletidyselectutf8vctrsviridisLitewithrzoo
Bayesian Likelihood-Based Inference for Time Series Extremes
Rendered fromlite-2-bayesian.Rmdusingknitr::rmarkdownon Nov 14 2024.Last update: 2022-05-16
Started: 2022-05-16
Frequentist Likelihood-Based Inference for Time Series Extremes
Rendered fromlite-1-frequentist.Rmdusingknitr::rmarkdownon Nov 14 2024.Last update: 2023-01-26
Started: 2022-05-16
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| lite: Likelihood-Based Inference for Time Series Extremes | lite-package _PACKAGE |
| Frequentist inference for the Bernoulli distribution | Bernoulli coef.Bernoulli fitBernoulli logLik.Bernoulli nobs.Bernoulli vcov.Bernoulli |
| Bayesian threshold-based inference for time series extremes | blite |
| Methods for objects of class '"blite"' | bliteMethods coef.blite confint.blite nobs.blite plot.blite print.summary.blite summary.blite vcov.blite |
| Functions for the 'estfun' method | estfun estfun.Bernoulli estfun.GP |
| Frequentist threshold-based inference for time series extremes | flite |
| Methods for objects of class '"flite"' | coef.flite confint.flite fliteMethods logLik.flite nobs.flite plot.flite print.summary.flite summary.flite vcov.flite |
| Frequentist inference for the generalised Pareto distribution | coef.GP fitGP generalisedPareto gpObsInfo logLik.GP nobs.GP vcov.GP |
| Functions for log-likelihood contributions | logLik.logLikVector logLikVector logLikVector.Bernoulli logLikVector.GP |
| Predictive inference for the largest value observed in N years. | predict.blite |
| Frequentist threshold-based inference for return levels | returnLevel |
| Methods for objects of class '"returnLevel"' | plot.returnLevel print.returnLevel print.summary.returnLevel returnLevelMethods summary.returnLevel |
